Recently, searching applications such as Internet search engines tend to be moving toward the use of full text search instead of relational search. This can be attributed to the simplicity and speed that is typically afforded by the use of full text searching. These searching applications tend to be context-agnostic. That is, search results tend to be obtained by using a searching function with keywords as the input thereto. The search results, which are also referred to as search hits, are typically defined as search results in which at least some of the keywords appear. These search hits are often ordered by a pre-computed score that takes into account certain attributes such as page ranking, creation or update time, frequency of access, and metadata associated with the results.
Some current research has been performed in an attempt to improve the user search experience by taking into account certain contextual information. However, the algorithms that have been used in these attempts are confined to either language-based algorithms or general topic-based algorithms.
Thus, there remains a need for a way to address these and other deficiencies that are associated with the prior art.